There is an old metaphor in investing — the “moat.” Warren Buffett popularized it: the idea that the best businesses are castles surrounded by deep, wide moats that keep competitors at bay.
For the past two decades, enterprise software companies built some of the most impressive moats in the history of capitalism. Sticky customers. Multi-year contracts. Switching costs so high that even dissatisfied clients stayed put. The moat wasn’t just deep — it was filled with concrete.
This morning, JP Morgan’s equity research team quietly suggested the concrete may be cracking. See also this recent Substack post by Jordi Visser.
In a note lowering price targets across their software coverage, the bank cited a striking phrase: “the exponential pace of AI proliferation raises doubts about competitive moats and the defensibility of software companies.”
They’re not alone in thinking this. But there’s something significant about seeing it written in the careful, hedged language of a major Wall Street research report.
When the analysts who model ten-year discounted cash flows start abandoning that framework — replacing it with simpler one- and two-year profitability multiples — it’s a signal worth decoding.
The shift in valuation methodology is itself the story. DCF analysis — the gold standard of software valuation for a generation — requires confidence in a company’s earnings trajectory over many years.
JP Morgan is saying, plainly, that they no longer have that confidence. The window of visibility has collapsed. When you can’t see more than a year or two out, you stop pretending you can.
“Investors are less comfortable underwriting defensive growth over multi-year periods.”
What’s driving this?
The suspicion — increasingly well-founded — that AI is not just a feature to be added to existing software products, but a force that restructures the value chain entirely.
If an AI agent can perform the function that previously required a $50,000-per-year SaaS subscription, the moat doesn’t just shrink. It evaporates. The castle becomes a historical curiosity.
Vertical software stocks — the specialized platforms serving specific industries like healthcare, construction, or legal — currently trade at 10 to 25 times EBITDA, according to the note. The S&P 500 as a whole trades at 15 times. The message embedded in those numbers is sobering: many of these once-premium businesses are being re-rated toward commodity valuations, and some may not have found their floor yet.
JP Morgan’s preferred companies in this environment are those with upside to 2026 revenue estimates and those they view as “defensive to AI proliferation.” That second phrase is the one I find myself turning over. It implies a new taxonomy is forming in the market — not growth vs. value, not cyclical vs. defensive, but AI-vulnerable vs. AI-resistant. That’s a categorization that didn’t meaningfully exist three years ago.
The moat metaphor may need an update. In the age of AI, the question is no longer how wide the moat is. It’s whether the castle itself still needs to exist.
Questions to Consider
- The Moat Inventory: If you were a software CEO this morning, which parts of your product would you genuinely consider defensible against AI substitution — and which would you privately admit are vulnerable?
- The Valuation Signal: When Wall Street abandons long-term DCF models in favor of near-term multiples, is that a temporary adjustment to uncertainty — or a permanent reset in how software businesses will be valued going forward?
- The New Taxonomy: JP Morgan implicitly divides the software world into AI-vulnerable and AI-resistant. What characteristics do you think actually define that divide — and can a company move from one category to the other?
- The Buffett Test: Buffett’s moat metaphor was built for a world of slow-moving competitive forces. Is the concept still useful in an era of exponential technology change, or do we need a new mental model entirely?
- The Timing Question: Is this re-rating of software companies a rational early response to a real structural shift — or is Wall Street, as it often does, overcorrecting in the short term for a change that will take much longer to fully materialize?
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